Triple
T5173080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Brent |
E116730
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Kingsbury |
E415096
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kingsbury | Statement: [River Brent, flowsThrough, Kingsbury]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kingsbury Context triple: [River Brent, flowsThrough, Kingsbury]
-
A.
Kingsbury
chosen
Kingsbury is a suburban district in northwest London, England, known for its residential character and proximity to Wembley.
-
B.
Lansbury
Lansbury is the surname most famously associated with British-American actress and singer Angela Lansbury, renowned for her work in film, theatre, and television.
-
C.
Kirkley
Kirkley is a coastal suburb and former village now forming part of the town of Lowestoft in Suffolk, England.
-
D.
Kearsley
Kearsley is a town in Greater Manchester, England, historically part of Lancashire and known for its industrial heritage.
-
E.
Kingswood
Kingswood is a suburban residential area in the borough of Reigate and Banstead in Surrey, England, known for its leafy streets and affluent character.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69bd445ff97c81909a2615cc56235470 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd796f7c308190a721e33aabd499ac |
completed | March 20, 2026, 4:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee077effc8190bdd5771db64d1578 |
completed | March 21, 2026, 6:16 p.m. |
Created at: March 20, 2026, 1:45 p.m.